A comprehensive 5-day hands-on workshop covering Large Language Models (LLMs) and Computer Vision with practical applications.
This workshop is designed for college students to gain practical experience with:
- Day 1: Foundations & Environment Setup
- Day 2: LLM Fine-Tuning & Applications
- Day 3: Computer Vision Deep Dive
- Day 4: Capstone Hackathon
- Day 5: Showcase & Next Steps (Virtual)
- Python 3.10+
- 8GB+ RAM recommended
- GPU access (Google Colab Pro recommended)
- Clone this repository:
git clone <repository-url>
cd ai-workshop- Create a virtual environment:
python -m venv workshop-env
source workshop-env/bin/activate # On Windows: workshop-env\Scripts\activate- Install requirements:
pip install -r requirements.txt- Test your environment:
python tests/test_environment.pyai-workshop/
├── src/ # Daily workshop materials
│ ├── day1/ # Foundations & Setup
│ ├── day2/ # LLM Fine-tuning & Apps
│ ├── day3/ # Computer Vision
│ ├── day4/ # Capstone Projects
│ ├── day5/ # Showcase
│ └── shared/ # Common utilities
├── docs/ # Documentation
├── assets/ # Images & presentations
└── tests/ # Environment tests
By the end of this workshop, students will:
- Build and deploy AI applications using Gradio
- Fine-tune LLMs for specific tasks
- Implement RAG (Retrieval-Augmented Generation) systems
- Train computer vision models with transfer learning
- Understand AI ethics and safety considerations
- Create a capstone project showcasing learned skills
This project is licensed under the MIT License - see the LICENSE file for details.
Please read our contributing guidelines and code of conduct before submitting pull requests.
Happy Learning! 🚀